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Current coronavirus disease-2019 (COVID-19) pandemic has caused massive loss of lives. Clinical trials of vaccines and drugs are currently being conducted around the world; however, till now no effective drug is available for COVID-19. Identification of key genes and perturbed pathways in COVID-19 may uncover potential drug targets and biomarkers. We aimed to identify key gene modules and hub targets involved in COVID-19. We have analyzed SARS-CoV-2 infected peripheral blood mononuclear cell (PBMC) transcriptomic data through gene coexpression analysis. We identified 1520 and 1733 differentially expressed genes (DEGs) from the GSE152418 and CRA002390 PBMC datasets, respectively (FDR < 0.05). We found four key gene modules and hub gene signature based on module membership (MMhub) statistics and protein–protein interaction (PPI) networks (PPIhub). Functional annotation by enrichment analysis of the genes of these modules demonstrated immune and inflammatory response biological processes enriched by the DEGs. The pathway analysis revealed the hub genes were enriched with the IL-17 signaling pathway, cytokine–cytokine receptor interaction pathways. Then, we demonstrated the classification performance of hub genes (PLK1, AURKB, AURKA, CDK1, CDC20, KIF11, CCNB1, KIF2C, DTL and CDC6) with accuracy >0.90 suggesting the biomarker potential of the hub genes. The regulatory network analysis showed transcription factors and microRNAs that target these hub genes. Finally, drug–gene interactions analysis suggests amsacrine, BRD-K68548958, naproxol, palbociclib and teniposide as the top-scored repurposed drugs. The identified biomarkers and pathways might be therapeutic targets to the COVID-19.

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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease, more commonly COVID-19 has emerged as a world health pandemic. There are couples of treatment methods for COVID-19, however, well-established drugs and vaccines are urgently needed to treat the COVID-19. The new drug discovery is a tremendous challenge; repurposing of existing drugs could shorten the time and expense compared with de novo drug development. In this study, we aimed to decode molecular signatures and pathways of the host cells in response to SARS-CoV-2 and the rapid identification of repurposable drugs using bioinformatics and network biology strategies. We have analyzed available transcriptomic RNA-seq COVID-19 data to identify differentially expressed genes (DEGs). We detected 177 DEGs specific for COVID-19 where 122 were upregulated and 55 were downregulated compared to control (FDR<0.05 and logFC ≥ 1). The DEGs were significantly involved in the immune and inflammatory response. The pathway analysis revealed the DEGs were found in influenza A, measles, cytokine signaling in the immune system, interleukin-4, interleukin −13, interleukin −17 signaling, and TNF signaling pathways. Protein-protein interaction analysis showed 10 hub genes (BIRC3, ICAM1, IRAK2, MAP3K8, S100A8, SOCS3, STAT5A, TNF, TNFAIP3, TNIP1). The regulatory network analysis showed significant transcription factors (TFs) that target DEGs, namely FOXC1, GATA2, YY1, FOXL1, NFKB1. Finally, drug repositioning analysis was performed with these 10 hub genes and showed that in silico validated three drugs with molecular docking. The transcriptomics signatures, molecular pathways, and regulatory biomolecules shed light on candidate biomarkers and drug targets which have potential roles to manage COVID-19. ICAM1 and TNFAIP3 were the key hubs that have demonstrated good binding affinities with repurposed drug candidates. Dabrafenib, radicicol, and AT-7519 were the top-scored repurposed drugs that showed efficient docking results when they tested with hub genes. The identified drugs should be further evaluated in molecular level wet-lab experiments in prior to clinical studies in the treatment of COVID-19.

Background: Naturally-occurring products derived from living organisms have been shown to modulate various pharmacological and biological activities. Natural products protect against various diseases, which could be used for therapeutic assistance. Autophagy, a lysosome-mediated self-digestion pathway, has been implicated in a range of pathophysiological conditions and has recently gained attention for its role in several neurodegenerative diseases. Methods: In this current review, we emphasized the recent progress made in our understanding of the molecular mechanism of autophagy in different cellular and mouse models using naturally-occurring autophagy modulators for the management of several neurodegenerative diseases. Results: Accumulating evidence has revealed that a wide variety of natural compounds such as alkaloids, polyphenols, terpenoids, xanthonoids, flavonoids, lignans, disaccharides, glycolipoproteins, and saponins are involved in the modulation of the autophagy signaling pathway. These natural products have been used to treat various neurodegenerative diseases such as Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, Amyotrophic lateral sclerosis, spinocerebellar ataxia, neuroblastoma, and glioblastoma. Although a number of synthetic autophagy regulators have been recognized as encouraging neurodegenerative therapeutic candidates, natural autophagy- regulating compounds have been of further interest as potential disease therapeutics, as they cause insignificant side effects. Conclusion: Existing in vitro and in vivo data are promising and highlight that naturally-occurring autophagyregulating compounds play an important role in the prevention and treatment of neurodegenerative disorders.

The head and neck squamous cell carcinoma (HNSCC) is one of the most common cancers in the world, but robust biomarkers and diagnostics are still not available. This study provides in-depth insights from systems biology analyses to identify molecular biomarker signatures to inform systematic drug targeting in HNSCC. Gene expression profiles from tumors and normal tissues of 22 patients with histological confirmation of nonmetastatic HNSCC were subjected to integrative analyses with genome-scale biomolecular networks (i.e., protein-protein interaction and transcriptional and post-transcriptional regulatory networks). We aimed to discover molecular signatures at RNA and protein levels, which could serve as potential drug targets for therapeutic innovation in the future. Eleven proteins, 5 transcription factors, and 20 microRNAs (miRNAs) came into prominence as potential drug targets. The differential expression profiles of these reporter biomolecules were cross-validated by independent RNA-Seq and miRNA-Seq datasets, and risk discrimination performance of the reporter biomolecules, BLNK, CCL2, E4F1, FOSL1, ISG15, MMP9, MYCN, MYH11, miR-1252, miR-29b, miR-29c, miR-3610, miR-431, and miR-523, was also evaluated. Using the transcriptome guided drug repositioning tool, geneXpharma, several candidate drugs were repurposed, including antineoplastic agents (e.g., gemcitabine and irinotecan), antidiabetics (e.g., rosiglitazone), dermatological agents (e.g., clocortolone and acitretin), and antipsychotics (e.g., risperidone), and binding affinities of the drugs to their potential targets were assessed using molecular docking analyses. The molecular signatures and repurposed drugs presented in this study warrant further attention for experimental studies since they offer significant potential as biomarkers and candidate therapeutics for precision medicine approaches to clinical management of HNSCC.

BackgroundAlzheimer’s disease (AD), one of the major causes of dementia, is an overwhelming neurodegenerative disease that particularly affects the brain, leading to memory loss and impairment of language and judgment capacity. The aim of the present study was to investigate the antioxidant and anticholinesterase properties of the leaves of Elatostema papillosum (EPL) and correlate with their phytochemical profiles, which are relevant to the treatment of AD.MethodsThe dried coarse powder of EPL was extracted with 80% methanol (EPL-M80) by cold extraction method. The resultant EPL-M80 was assessed for acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) inhibitory activity by the Ellman method. The antioxidant activity was determined by DPPH (1, 1-diphenyl-2-picrylhydrazyl) and hydroxyl radical scavenging assays. Quantitative phytochemical (phenolic and flavonoid contents) analysis of endogenous substances in EPL-M80 was performed by standard spectrophotometric methods.ResultsEPL-M80 significantly (p < 0.05) inhibited AChE and BChE activity with IC50 of 165.40 ± 4.01 and 213.81 ± 3.57 μg/mL, respectively in a dose-dependent manner. Additionally, EPL-M80 exhibited strong radical scavenging activity against DPPH (IC50 = 32.35 ± 0.68 μg/mL) and hydroxyl radical (IC50 = 19.67 ± 1.42 μg/mL) when compared to that of standards. EPL-M80 was found to be rich in phenolic (23.74 mg gallic acid equivalent/g of dry extract) and flavonoid (31.18 mg quercetin equivalent/g of dry extract) content. Furthermore, a positive correlation (p < 0.001) was observed between the total phenolics and antioxidant as well as the anticholinesterase potential.ConclusionsThe marked inhibition of AChE and BChE, and potent antioxidant activity of the leaves of Elatostema papillosum highlight its potential to provide an effective treatment for AD.

Background: Autism spectrum disorder (ASD) is a neurodevelopmental disorder with deficits in social communication ability and repetitive behavior. The pathophysiological events involved in the brain of this complex disease are still unclear. Methods: In this study, we aimed to profile the gene expression signatures of brain cortex of ASD patients, by using two publicly available RNA-seq studies, in order to discover new ASD-related genes. Results: We detected 1567 differentially expressed genes (DEGs) by meta-analysis, where 1194 were upregulated and 373 were downregulated genes. Several ASD-related genes previously reported were also identified. Our meta-analysis identified 235 new DEGs that were not detected using the individual RNA-seq studies used. Some of those genes, including seven DEGs (PAK1, DNAH17, DOCK8, DAPP1, PCDHAC2, and ERBIN, SLC7A7), have been confirmed in previous reports to be associated with ASD. Gene Ontology (GO) and pathways analysis showed several molecular pathways enriched by the DEGs, namely, osteoclast differentiation, TNF signaling pathway, complement and coagulation cascade. Topological analysis of protein–protein interaction of the ASD brain cortex revealed proteomics hub gene signatures: MYC, TP53, HDAC1, CDK2, BAG3, CDKN1A, GABARAPL1, EZH2, VIM, and TRAF1. We also identified the transcriptional factors (TFs) regulating DEGs, namely, FOXC1, GATA2, YY1, FOXL1, USF2, NFIC, NFKB1, E2F1, TFAP2A, HINFP. Conclusion: Novel core genes and molecular signatures involved with ASD were identified by our meta-analysis.